Home ›
Entities
› academia
› TGMIL: A hybrid multi-instance learning model based on the Transformer and the Graph Attention Network for whole-slide images classification of renal cell carcinoma
TGMIL: A hybrid multi-instance learning model based on the Transformer and the Graph Attention Network for whole-slide images classification of renal cell carcinoma
Research article (Computer Methods and Programs in Biomedicine, 2023) · cited 24× · AI/ML
TGMIL: A hybrid multi-instance learning model based on the Transformer and the Graph Attention Network for whole-slide images classification of renal cell carcinoma
Summary
TGMIL: A hybrid multi-instance learning model based on the Transformer and the Graph Attention Network for whole-slide images classification of renal cell carcinoma is a scholarly article[1].
Key Facts
TGMIL: A hybrid multi-instance learning model based on the Transformer and the Graph Attention Network for whole-slide images classification of renal cell carcinoma's instance of is recorded as scholarly article[2].
References
Programmatic citations — every numbered marker resolves to a verifiable graph row below.
Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.
APA4ort.xyz Knowledge Graph. (2026). TGMIL: A hybrid multi-instance learning model based on the Transformer and the Graph Attention Network for whole-slide images classification of renal cell carcinoma. Retrieved May 24, 2026, from https://4ort.xyz/entity/tgmil-a-hybrid-multi-instance-learning-model-based-on-the-transformer-and-the-graph-attention-network-for-whole-slide-im
MLA“TGMIL: A hybrid multi-instance learning model based on the Transformer and the Graph Attention Network for whole-slide images classification of renal cell carcinoma.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/tgmil-a-hybrid-multi-instance-learning-model-based-on-the-transformer-and-the-graph-attention-network-for-whole-slide-im.
BibTeX@misc{4ortxyz_tgmil-a-hybrid-multi-instance-learning-model-based-on-the-transformer-and-the-graph-attention-network-for-whole-slide-im_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{TGMIL: A hybrid multi-instance learning model based on the Transformer and the Graph Attention Network for whole-slide images classification of renal cell carcinoma}}, year = {2026}, url = {https://4ort.xyz/entity/tgmil-a-hybrid-multi-instance-learning-model-based-on-the-transformer-and-the-graph-attention-network-for-whole-slide-im}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): TGMIL: A hybrid multi-instance learning model based on the Transformer and the Graph Attention Network for whole-slide images classification of renal cell carcinoma — https://4ort.xyz/entity/tgmil-a-hybrid-multi-instance-learning-model-based-on-the-transformer-and-the-graph-attention-network-for-whole-slide-im (retrieved 2026-05-24)
